Impact of Optimal Storage Allocation on Price Volatility in Energy-Only Electricity Markets

Abstract

Abstract-Recent studies show that the fast growing expansion of wind power generation may lead to extremely high levels of price volatility in wholesale electricity markets. Storage technologies, regardless of their specific forms e.g. pump-storage hydro, large-scale or distributed batteries, are capable of alleviating the extreme price volatility levels due to their energy usage time shifting, fast-ramping and price arbitrage capabilities. In this paper, we propose a stochastic bi-level optimization model to find the optimal nodal storage capacities required to achieve a certain price volatility level in a highly volatile electricity market. The decision on storage capacities is made in the upper level problem and the operation of strategic/regulated generation, storage and transmission players is modeled at the lower level problem using an extended Cournot-based stochastic game. The South Australia (SA) electricity market, which has recently experienced high levels of price volatility, is considered as the case study for the proposed storage allocation framework. Our numerical results indicate that 80% price volatility reduction in SA electricity market can be achieved by installing either 340 MWh regulated storage or 420 MWh strategic storage. In other words, regulated storage firms are more efficient in reducing the price volatility than strategic storage firms.

Operating and Investment Models for Energy Storage Systems

“…The impact of optimal allocation of both strategically and non-strategically behaving ESS on price volatility in energy-only markets was investigated by Masoumzadeh et al [124]. They showed that, although an ESS is able to decrease price volatility, it does not remove it completely, and the positive impact stops when the ESS reaches the profitability limit.…”

Storage-Transmission Joint Planning Method to Deal with Insufficient Flexibility and Transmission Congestion

“…In recent years, many scholars have carried out a series of fruitful work to alleviate the wind curtailment problem, such as energy storage optimization configuration (Dicorato et al, 2012;Del Rosso and Eckroad, 2014;Zheng et al, 2015b;Lu et al, 2018;Masoumzadeh et al, 2018;Al Ahmad and Sirjani, 2020;Padhee et al, 2020), and joint planning of energy storage and transmission grids (Zheng et al, 2015a;Qiu et al, 2017;Bustos et al, 2018;Dvorkin et al, 2018;Jorgenson et al, 2018;Yacar et al, 2018;Zhang and Conejo, 2018;Nikoobakht and Aghaei, 2019;Sima et al, 2019;Wu and Jiang, 2019). In terms of energy storage optimization configuration, Padhee et al, (2020) proposed a hybrid energy storage optimization configuration method for the intermittency and uncertainty of renewable energy, while Al Ahmad and Sirjani (2020) combined the discretization method, multi-objective hybrid particle swarm algorithm and nondominated sorting genetic algorithm.…”

“…The fluctuation of renewable energy output brings about the problem of fluctuations in electricity prices. Masoumzadeh et al, (2018) using energy storage makes the electricity market price fluctuate at a certain level. Energy storage configuration can not only increase the flexibility of the system (Lu et al, 2018), but also delay the construction of transmission lines (Del Rosso and Eckroad, 2014), so the joint planning of energy storage and transmission grids has attracted extensive research interest.…”

The Role of Demand-Side Flexibility in Hedging Electricity Price Volatility in Distribution Grids

“…Similarly, [9] focuses on analyzing the consumer reaction and their willingness to shift demand under demand response programs. In contrast, the optimal size of energy storage as a demand-side flexibility resource for addressing price volatility in a renewable generation-dominant electricity market is investigated in [10].…”